11 to 20 of 53 Results
Müller, Christoph, 2024, "SFB/Transregio 161 Data Management Plan 2023-2027", https://doi.org/10.18419/DARUS-4452, DaRUS, V1
The participating universities in SFB/Transregio 161 acknowledge the general importance of re-search data management as a vital issue for all of their work and provide increasing central sup-port for long-term accessibility and reusability of data, documentation of methods and tools and privacy protection. However, technical and organisational offe... |
Jul 30, 2024 - Visualisierungsinstitut der Universität Stuttgart
Gralka, Patrick; Müller, Christoph; Heinemann, Moritz; Reina, Guido; Weiskopf, Daniel; Ertl, Thomas, 2024, "Supplemental Material for "Power Overwhelming: The One With the Oscilloscopes"", https://doi.org/10.18419/DARUS-4256, DaRUS, V1, UNF:6:+e/WFL9E6WB+2FvGNOvcGA== [fileUNF]
Supplemental Material for "Power Overwhelming: The One With the Oscilloscopes". Contains the aggregated energy consumption data from the experiments in the paper. The application under test was MegaMol with two OpenGL-based sphere rasterization rendering methods (data static on GPU, data streaming to GPU) and OptiX-based sphere ray tracing. |
Jun 21, 2024 - SFB-TRR 161 D04 "Quantitative Aspects of Immersive Analytics for the Life Sciences"
Bienroth, Denis; Charitakis, Natalie; Jaeger-Honz, Sabrina; Garkov, Dimitar; Elliott, David; Porrello, Enzo R.; Klein, Karsten; Nim, Hieu T.; Schreiber, Falk; Ramialison, Mirana, 2024, "Spatially Resolved Transcriptomics Mining in 3D and Virtual Reality Environments with VR-Omics (Software and Data)", https://doi.org/10.18419/DARUS-4254, DaRUS, V1
Here, we summarise available data and source code regarding the publication "Spatially Resolved Transcriptomics Mining in 3D and Virtual Reality Environments with VR-Omics". Abstract Spatially resolved transcriptomics (SRT) technologies produce complex, multi-dimensional data sets of gene expression information that can be obtained at subcellular s... |
Jun 19, 2024 - SFB-TRR 161 D04 "Quantitative Aspects of Immersive Analytics for the Life Sciences"
Jaeger-Honz, Sabrina; Klein, Karsten; Schreiber, Falk, 2024, "Research Data Summary for: "Systematic analysis, aggregation and visualisation of interaction fingerprints for molecular dynamics simulation data"", https://doi.org/10.18419/DARUS-4251, DaRUS, V1
Here, we summarise available data and source code regarding the publication "Systematic analysis, aggregation and visualisation of interaction fingerprints for molecular dynamics simulation data". Abstract Computational methods such as molecular docking or molecular dynamics (MD) simulations have been developed to simulate and explore the interacti... |
Jun 18, 2024 - SFB-TRR 161 D04 "Quantitative Aspects of Immersive Analytics for the Life Sciences"
Kern, Martin; Jaeger-Honz, Sabrina; Schreiber, Falk; Sommer, Björn, 2024, "Research Data: "APL@voro—interactive visualization and analysis of cell membrane simulations"", https://doi.org/10.18419/DARUS-4252, DaRUS, V1
Here, we summarise available data and source code regarding the publication "APL@voro—interactive visualization and analysis of cell membrane simulations". Abstract Molecular dynamics (MD) simulations of cell membranes allow for a better understanding of complex processes such as changing membrane dynamics, lipid rafts and the incorporation/passing... |
Apr 8, 2024 - SFB-TRR 161 A07 "Visual Attention Modeling for Optimization of Information Visualizations"
Wang, Yao; Bulling, Andreas, 2024, "VisRecall++: Analysing and Predicting Recallability of Information Visualisations from Gaze Behaviour (Dataset and Reproduction Data)", https://doi.org/10.18419/DARUS-3138, DaRUS, V1, UNF:6:NwphGtoYrBQqd2TyRh0OHA== [fileUNF]
This dataset contains stimuli and collected participant data of VisRecall++. The structure of the dataset is described in the README-File. Further, if you are interested in related codes of the publication, you can find a copy of the code repository (see Metadata for Research Software) within this dataset. |
Mar 22, 2024 - SFB-TRR 161 A07 "Visual Attention Modeling for Optimization of Information Visualizations"
Wang, Yao; Bulling, Andreas, 2024, "Saliency3D: A 3D Saliency Dataset Collected on Screen (Dataset and Experiment Application)", https://doi.org/10.18419/DARUS-4101, DaRUS, V1
While visual saliency has recently been studied in 3D, the experimental setup for collecting 3D saliency data can be expensive and cumbersome. To address this challenge, we propose a novel experimental design that utilizes an eye tracker on a screen to collect 3D saliency data. Our experimental design reduces the cost and complexity of 3D saliency... |
Krake, Tim; Klötzl, Daniel; Hägele, David; Weiskopf, Daniel, 2024, "Uncertainty-Aware Seasonal-Trend Decomposition Based on Loess - Supplemental Material", https://doi.org/10.18419/DARUS-3845, DaRUS, V1
In this supplemental material, we provide the appendix (mathematically exact propagation of uncertainty) and the video material for uncertainty-aware seasonal-trend decomposition based on loess (UASTL). This material complements the main document: The paper on Uncertainty-Aware Seasonal-Trend Decomposition Based on Loess. |
Mar 1, 2024 - SFB-TRR 161 INF "Collaboration Infrastructure"
Becher, Michael; Müller, Christoph; Reina, Guido; Weiskopf, Daniel; Ertl, Thomas, 2024, "Your visualisations are going places: Performance data for scientific visualisation on gaming consoles", https://doi.org/10.18419/DARUS-4003, DaRUS, V1
The data set contains performance data (mainly frame times) for rendering spherical glyphs and scalar fields on Xbox Series consoles, mobile game consoles and a reference PC with different GPUs. |
Mikheev, Vladimir; Skukies, Rene; Ehinger, Benedikt, 2023, "Supplementary material: "The Art of Brainwaves: A Survey on Event-Related Potential Visualization Practices"", https://doi.org/10.18419/DARUS-3729, DaRUS, V2, UNF:6:+qePfVjlqif+DUSlAZSsrw== [fileUNF]
The purpose related to this dataset is to investigate the state of visualization in ERP (Event-Related Potential) research. The investigation was conducted through an online questionnaire administered via LimeSurvey Community Edition v5.4.7, hosted by the University of Stuttgart. The survey was designed to gather information about participants' exp... |
